A variety of sequence model architectures from scratch in PyTorch
Sequence Models This repository implements a variety of sequence model architectures from scratch in PyTorch. Effort has been put to make the code well structured so that it can serve as learning material. The training loop implements the learner design pattern from fast.ai in pure PyTorch, with access to the loop provided through callbacks. Detailed logging and graphs are also provided with python logging and wandb. Additional implementations will be added. Setup Using Miniconda/Anaconda: cd path_to_repo conda create –name –file […]
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